The answer is to increase the number of DPUs for the job, but the most impactful cost-saving action is implementing column pruning in your AWS Glue ETL scripts. Column pruning reduces the amount of data read from Amazon S3 by specifying only the columns needed for the transformation, which minimizes I/O and network overhead, directly lowering costs and improving job performance, especially when processing large CSV files. On the AWS Certified Data Engineer Associate DEA-C01 exam, this concept tests your understanding of how to optimize costs in AWS Glue ETL jobs by reducing data scanned, a common trap being that more DPUs always save money—they actually increase cost unless paired with pruning to shorten runtime. A key memory tip is "prune to save, scale to speed": prune columns first to cut data volume, then adjust DPUs to balance performance and cost.
DEA-C01 Data Ingestion and Transformation Practice Question
This DEA-C01 practice question tests your understanding of data ingestion and transformation. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company uses AWS Glue to perform ETL on data stored in Amazon S3. The Glue job reads CSV files, converts them to Parquet, and partitions by date. The job runs daily and processes about 500 GB of data. The team wants to optimize costs and performance. Which three actions should the team take? (Select THREE.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use column pruning to read only necessary columns in the Glue script.
Option B is correct because column pruning in AWS Glue scripts reduces the amount of data read from Amazon S3 by specifying only the columns needed for the ETL transformation. This minimizes I/O and network overhead, directly lowering costs and improving job performance, especially when processing large CSV files.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✗
Increase the Spark shuffle partitions to 500.
Why it's wrong here
More partitions can increase overhead; optimal value depends on data.
✓
Use column pruning to read only necessary columns in the Glue script.
Why this is correct
Reduces data scanned and improves performance.
Related concept
Read the scenario before looking for a memorised answer.
✓
Use G.1X or G.2X worker types for better performance.
Why this is correct
These worker types offer more memory for complex transformations.
Related concept
Read the scenario before looking for a memorised answer.
✓
Increase the number of DPUs for the job.
Why this is correct
More DPUs parallelize processing for large datasets.
Related concept
Read the scenario before looking for a memorised answer.
✗
Write the output as JSON instead of Parquet to avoid compression overhead.
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often confuse increasing DPUs or shuffle partitions as a universal performance fix, but AWS Glue's cost optimization relies on reducing data processed (column pruning) and choosing appropriate worker types for the workload, not simply scaling resources.
Detailed technical explanation
How to think about this question
Column pruning leverages Apache Spark's predicate pushdown and Parquet's columnar storage format to skip reading entire columns from S3, reducing data scanned per task. In practice, for a 500 GB CSV dataset with 50 columns but only 10 needed, column pruning can cut I/O by 80%, directly lowering S3 GET request costs and job runtime. AWS Glue also supports pushdown predicates for partition filtering, which further optimizes performance when combined with column pruning.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Data Ingestion and Transformation — This question tests Data Ingestion and Transformation — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Use column pruning to read only necessary columns in the Glue script. — Option B is correct because column pruning in AWS Glue scripts reduces the amount of data read from Amazon S3 by specifying only the columns needed for the ETL transformation. This minimizes I/O and network overhead, directly lowering costs and improving job performance, especially when processing large CSV files.
What should I do if I get this DEA-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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